• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1997-2002
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• 2007

This study selected soil erosion source area of Dechung basin by soil erosion estimation model and field survey for effective soil conservation planning and management. First, unit soil erosion amount of Dechung basin is analyzed using RUSLE (Revised Universal Soil Loss Equation) model based on DEM (Digital Elevation Model), soil map, landcover map and rainfall data. Soil erosion model is difficult to analyze the tracing route of soil particle and to consider the characteristics of bank condition and the types of crop, multidirectional field survey is necessary to choice the soil erosion source area. As the result of analysis of modeling value and field survey, Mujunamde-, Wondang-, Geumpyong stream are selected in the soil erosion source area of Dechung basin. Especially, these areas show steep slope in river boundary and cultivation condition of crop is also weakness to soil erosion in the field survey.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.413-416
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• 2006

This paper presents a strategic approach to effective soil conservation planning and management. To do this, the soil loss model, Revised Universal Soil Loss Equation (RUSLE) was used to quantify soil erosion in two basins (Andong and Imha basin), which are distinct in terms of sedimentation in the reservoir of each basin. Areas with high soil erosion potential were analyzed on the basis of land surface characteristics handled by geographic information system (GIS), especially dividing the basin into several sub-basins and then examination was emphasized near the river channel (water-pollutant buffering zone), along which human activities are large. Modeling results show the approach suggested herein provides a basis and guideline for choosing prior erosion risk areas to be examined for soil conservation planning and management. Also, this approach is relatively simple and has wide practical applicability.

• Spatial Information Research
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• v.10 no.1
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• pp.139-152
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• 2002

The purpose of this study is to estimate temporal soil loss change according to long-term land cover changes using G1S and RS. Revised USLE(Universal Soil Loss Equation) factors were prepared by using point rainfall data, DEM(Digital Elevation Model), soil map and land cover map. During the past two decades, land cover changes were traced by using Landsat MSS and TM data. As a result, forest area in 2000 has decreased 25.3 $km^2$ compared with that in 1990. Soil loss has decreased 3751.2 tou/yr. On the other hand, upland area has increased 22.5 $km^2$. Soil loss of upland has increased 5395.4 to/yr. Therefore, soil loss in 2000 increased 6.3 kg/$m^2$/yr compared with that in 1990. This was mainly caused by the increased upland area.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.80-80
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• 2022

본 연구는 한강유역 (35,770 km²)을 대상으로 RUSLE (Revised Universal Soil Loss Equation)과 WATEM/SEDEM (The Water and Tillage Erosion Model and Sediment Delivery Model)의 유사이동식을 활용하여 인간활동과 기후변화로 인한 유사량을 평가하였다. 대상유역에 영향을 주는 16곳의 기상관측소에서 제공하는 분 단위 누적강수량 (2000-2019), 농촌진흥청 토양도, 국토지리정보원 DEM (Digital Elevation Model), 환경공간정보서비스 (EGIS) 2020년 세분류 토지이용도를 활용하여 RUSLE과 WATEM/SEDEM 유사이동식에 필요한 강우침식인자(R), 토양침식인자 (K), 지형인자 (L·S), 식생피복인자 (C), 그리고 보전관리인자 (P)를 구축하였으며, SWAT (Soil and Water Assessment Tool)으로 모의한 표준유역 단위 연도별(2000-2019) 유사량 결과를 기준으로 WATEM/SEDEM 유사량 계수 (KTC)를 검·보정하였다. 토양침식 산정 입력자료 중 강우량으로 산정하는 강우침식인자는 기후변화를 보여주는 인자, 토지피복에 따라 다른 식생피복인자와 보전관리인자는 인간활동을 나타내는 인자로 설정하였다. 강우침식인자는 2010년대 평균값을 활용하여 현재의 유사량을 평가하였으며, 분 단위 자료가 없는 과거의 경우 직접적인 계산에 어려움이 있어, 연평균 강수량과의 관계로 추정한 1980년대 평균값을 활용하여 기후변화로 인한 영향을 평가하였다. 식생피복인자와 보전관리인자는 1980년대 토지이용도를 활용하여 산정한 결과로 인간활동에 의한 유사량 평가에 사용되었다. 대상유역의 유사량은 RUSLE 모형의 토양침식량과 WATEM/SEDEM 유사이동량을 mass balance로 분석하며, 다른 인자들은 고정한 상태로 과거 강우침식인자, 식생피복인자와 보전관리인자를 적용하여 인간활동과 기후변화로 인한 유사량 변화를 분석하고자 한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.341-347
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• 2006

Geographically Imha basin is adjacent to Andong basin, but the occurrence of turbid water in each reservoir by storm events shows big differences. Hence, it is very important to identify the reason for these large differences. This study compared and analyzed soil erosion using the semi-empirical soil erosion model, RUSLE for both Imha and Andong basin, especially with emphasis on high-density turbid water. The agricultural district, which is the most vulnerable to soil erosion, was intensively analyzed based on land cover map produced by Ministry of Environment. As a result, the portion of the agricultural area is 11.88% for Andong basin, while it is 14.95% for Imha basin. Also all RUSLE factors excepts practice factor turned out to be higher for Imha basin. This means that the basin characteristics such as soil texture, terrain, and land cover for Imha basin is more vulnerable to soil erosion. Estimation of soil erosion by RUSLE for Andong and Imha basin is 1,275,806 ton and 1,501,608 ton, respectively, showing higher soil erosion by 225,802 ton for Imha basin.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3B
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• pp.221-232
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• 2011

Applicability of three soil erosion models for burnt hillslopes was evaluated. The models were estimated with the data from plots established after tremendous wildfire occurred in the east coastal region. Soil erosion and surface runoff were simulated by the Water Erosion Prediction Project (WEPP) and the Revised Universal Soil Loss Equation (RUSLE) of application mode for disturbed forest areas and the Soil Erosion Model for Mountain Areas (SEMMA) developed for burnt hillslopes. Simulated sediment yield and surface runoff were compared with the measured those. In maximum value of sediment yield, three models was under-predicted and RUSLE and WEPP had difference of over two times. SEMMA showed the best model response coefficient, determination coefficient and the model efficiency. In application of models to the soil erosion according to the elapsed year after wildfire, all models were underestimated in initial stage disturbed by wildfire. Evaluation of models in this burnt hillslopes was shown the tends to under-predict soil erosion for larger measured values. Although a lot of sediment can be generated in small rainfall event as fine-grained soil of the high water repellency was exposed excessively right after wildfire, this under-prediction was shown that those models have a limit to estimate the weighted factors by wildfire.

• Journal of Korea Water Resources Association
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• v.57 no.6
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• pp.421-435
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• 2024

In April 2023, a wildfire broke out in Gangneung located in the east coast region due to the influence of the Yanggang-local wind. In this study, GIS-based RUSLE(Revised Universal Soil Loss Equation) and SEMMA (Soil Erosion Model for Mountain Areas) were used to evaluate the erosion rate due to vegetation recovery in a small watershed of the Gangneung WUI(Wildland-Urban Interface) fire. The small watershed of WUI fire has a low altitude range of 10-30 m and the average slope of 10.0±7.4° which corresponds to a gentle slope. The soil texture was loamy sand with a high organic content and the deep soil depth. As herbaceous layer regenerated profusely in the gully after the wildfire, the NDVI (Normalized Difference Vegetation Index) reached a maximum of 0.55. Simulation results of erosion rates showed that RUSLE ranged from 0.07-94.9 t/ha/storm and SEMMA ranged from 0.24-83.6 t/ha/storm. RUSLE overestimated the average erosion rate by 1.19-1.48 times compared to SEMMA. The erosion rates were estimated to be high in the middle slope where burned pine trees were widely distributed and the slope was steep and to be relatively low in the hollow below the gully where herbaceous layer recovers rapidly. SEMMA showed a rapid increase in erosion sensitivity under at certain vegetation covers with NDVI below 0.25 (Ic = 0.35) on post-fire hillslopes. Gentle slopes with high organic content and rapid recovery of natural vegetation had relatively low erosion rate compared to steep slopes. As subsequent infrastructure and human damages due to sediment disaster by heavy rain is anticipated in WUI fire areas, the research results may be used as basic data for targeted management and decision making on the implementation of emergency treatment after the wildfire.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.529-533
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• 2008

본 연구는 미래기후변화가 공간해상도(5, 10, 30m)에 따른 토양유실량의 변화에 미치는 영향을 분석하고 자하였다. 연구대상지역은 경안천 최상류에 위치한 $1.16km^2$의 농촌 소유역을 대상으로 공간해상도별(5, 10, 30m) RS 및 GIS 자료를 생성하고, GIS 기반의 RUSLE(Revised Universal Soil Loss Equation) 모형을 채택하여 토양유실량을 분석하였다. 기후변화 시나리오는 IPCC(Intergovernmental Panel on Climate Change)에 서 제공하는 GCM(Global climate model) 중에서 MIROC3.2 hire의 A1B, B1 시나리오를 이용하였으며, 과거 30년간(1977-2006)의 기상자료 통계정보를 기준으로 Change Factor Downscaling 기법을 적용하여 2020s년 (2010-2039), 2050s년(2040-2069), 2080s년(2069-2099) 전후의 각 30년간의 미래 강우량을 재생산하여 사용하였다. 그 결과 강수량은 2080s년에 A1B 시나리오의 경우 연평균 강수량은 270.37mm, 최대 강수량은 65.71mm 증가하였고, B1 시나리오의 경우 연평균 강수량은 37.11mm, 최대 강수량은 48.46mm 증가하는 것으로 나타났다. 구축한 미래 강우량을 RUSLE 인자 중 R 인자에 적용하여 2020s년, 2050s년, 2080s년의 토양유실량을 분석한 결과, 미래강수량이 증가함에 따라 공간해상도별 토양유실량도 증가하는 것으로 분석되었다. 평균토양유실량을 시나리오별로 보면, A1B 시나리오의 경우 2080s을 기준으로 1/5,000 scale에서는 약 0.18 ton/ha/year, 1/25,000 scale에서는 약 0.07 ton/ha/year, 1/50,000 scale에서는 약 0.07 ton/ha/year의 유실량이 각 공간해상도별로 증가하였다. B1 시나리오의 경우 2080s을 기준으로 1/5,000 scale에서는 약 0.03 ton/ha/year, 1/25,000 scale에서는 약 0.01 ton/ha/year, 1/50,000 scale에서는 약 0.01 ton/ha/year의 토양유실량이 증가한 것으로 분석되었다.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.3
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• pp.3-10
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• 2010

The development of various spatial information and GIS has led to the research on interpretation of natural phenomena and correlational studies. This study is aimed to analyze the correlation between RUSLE(Revised Universal Soil Loss Equation) around Nakdong River area during the period of 1955 to 2005 and the amount of area change in the islets at the estuary terrain calculated in the study "Change Detection at the Nakdong Estuary Delta using Satellite Image and GIS". For the calculation of RUSLE, The 'Revised-USLE' model, a modified USLE model commonly used in Korea was used. For the rainfall erosion factor to calculate and compare the area of islets, the actual observation data for one year before the observation of satellite image from all observatories across Korea was used. The correlation coefficient between RUSLE and area change of islets was 0.57 for Jinwoo Islet; 0.7 for Sinja Islet; 0.87 for Doyodeung. This results showed that there was a great influence from Doyodeung where the main water way of Nakdong River runs. This study showed that the study using USLE for various fields and through identifying the characteristics of each factor is useful to understand natural phenomenon in practice.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.85-85
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• 2020

South Korea experiences few large scale erosion and sedimentation problems, however, there are numerous local sedimentation problems. A reliable and consistent approach to modelling and management for sediment processes are desirable in the country. In this study, field measurements of sediment concentration from 34 alluvial river basins in South Korea were used with the Modified Einstein Procedure (MEP) to determine the total sediment load at the sampling locations. And then the Flow Duration-Sediment Rating Curve (FD-SRC) method was used to estimate the specific degradation for all gauging stations. The specific degradation of most rivers were found to be typically 50-300 tons/㎢·yr. A model tree data mining technique was applied to develop a model for the specific degradation based on various watershed characteristics of each watershed from GIS analysis. The meaningful parameters are: 1) elevation at the middle relative area of the hypsometric curve [m], 2) percentage of wetland and water [%], 3) percentage of urbanized area [%], and 4) Main stream length [km]. The Root Mean Square Error (RMSE) of existing models is in excess of 1,250 tons/㎢·yr and the RMSE of the proposed model with 6 additional validations decreased to 65 tons/㎢·yr. Erosion loss maps from the Revised Universal Soil Loss Equation (RUSLE), satellite images, and aerial photographs were used to delineate the geospatial features affecting erosion and sedimentation. The results of the geospatial analysis clearly shows that the high risk erosion area (hill slopes and construction sites at urbanized area) and sedimentation features (wetlands and agricultural reservoirs). The result of physiographical analysis also indicates that the watershed morphometric characteristic well explain the sediment transport. Sustainable management with the data mining methodologies and geospatial analysis could be helpful to solve various erosion and sedimentation problems under different conditions.